Case Study: Karlsruhe Institute of Technology achieves personalized intranasal airflow simulations and diagnostic insight with Materialise's Mimics Innovation Suite

Innovative Patient-Specific Intranasal Flow Simulations

Karlsruhe Institute of Technology faced the challenge of turning complex CT scans of the human nasal cavity into reliable models for intranasal airflow simulation—shapes too fine for scanners to capture fully and a preprocessing/initialization workflow that must handle voxel-based LBM simulations. To address this, the research team used Materialise’s Mimics Innovation Suite together with 3-matic and an automated grid-generation/initialization concept to segment, reconstruct and prepare the anatomy for numerical simulation.

Materialise’s tools automated high-quality segmentation and helped reconstruct thin tissues and small cavities from incomplete CT data, while the workflow (combined with OpenLB for voxel meshes) enabled robust LBM simulations of nasal expiration. The simulations were validated against experimental and patient measurements, produced new insights into airflow, and directly supported a personalized diagnosis by locating a stenosis in one subject—demonstrating time savings, accurate reconstruction, and measurable clinical impact enabled by Materialise.

Karlsruhe Institute of Technology

Krause

Karlsruhe Institute of Technology